few last things

[valse.git] / pkg / R / initSmallEM.R

#' initialization of the EM algorithm
#'
#' @param k number of components
#' @param X matrix of covariates (of size n*p)
#' @param Y matrix of responses (of size n*m)
#'
#' @return a list with phiInit, rhoInit, piInit, gamInit
#' @export
#' @importFrom methods new
#' @importFrom stats cutree dist hclust runif
initSmallEM = function(k,X,Y)
{
	n = nrow(Y)
	m = ncol(Y)
	p = ncol(X)
  
	Zinit1 = array(0, dim=c(n,20))
	betaInit1 = array(0, dim=c(p,m,k,20))
	sigmaInit1 = array(0, dim = c(m,m,k,20))
	phiInit1 = array(0, dim = c(p,m,k,20))
	rhoInit1 = array(0, dim = c(m,m,k,20))
	Gam = matrix(0, n, k)
	piInit1 = matrix(0,20,k)
	gamInit1 = array(0, dim=c(n,k,20))
	LLFinit1 = list()

	require(MASS) #Moore-Penrose generalized inverse of matrix
	for(repet in 1:20)
	{
	  distance_clus = dist(X)
	  tree_hier = hclust(distance_clus)
	  Zinit1[,repet] = cutree(tree_hier, k)

		for(r in 1:k)
		{
			Z = Zinit1[,repet]
			Z_indice = seq_len(n)[Z == r] #renvoit les indices où Z==r
			if (length(Z_indice) == 1) {
			  betaInit1[,,r,repet] = ginv(crossprod(t(X[Z_indice,]))) %*%
			    crossprod(t(X[Z_indice,]), Y[Z_indice,])
			} else {
			betaInit1[,,r,repet] = ginv(crossprod(X[Z_indice,])) %*%
				crossprod(X[Z_indice,], Y[Z_indice,])
			}
			sigmaInit1[,,r,repet] = diag(m)
			phiInit1[,,r,repet] = betaInit1[,,r,repet] #/ sigmaInit1[,,r,repet]
			rhoInit1[,,r,repet] = solve(sigmaInit1[,,r,repet])
			piInit1[repet,r] = mean(Z == r)
		}
		
		for(i in 1:n)
		{
			for(r in 1:k)
			{
				dotProduct = tcrossprod(Y[i,]%*%rhoInit1[,,r,repet]-X[i,]%*%phiInit1[,,r,repet])
				Gam[i,r] = piInit1[repet,r]*det(rhoInit1[,,r,repet])*exp(-0.5*dotProduct)
			}
			sumGamI = sum(Gam[i,])
			gamInit1[i,,repet]= Gam[i,] / sumGamI
		}
		
		miniInit = 10
		maxiInit = 11
		
		#new_EMG = .Call("EMGLLF_core",phiInit1[,,,repet],rhoInit1[,,,repet],piInit1[repet,],
#			gamInit1[,,repet],miniInit,maxiInit,1,0,X,Y,1e-4)
		new_EMG = EMGLLF(phiInit1[,,,repet],rhoInit1[,,,repet],piInit1[repet,],gamInit1[,,repet],miniInit,maxiInit,1,0,X,Y,1e-4)
		LLFEessai = new_EMG$LLF
		LLFinit1[repet] = LLFEessai[length(LLFEessai)]
	}

	b = which.max(LLFinit1)
	phiInit = phiInit1[,,,b]
	rhoInit = rhoInit1[,,,b]
	piInit = piInit1[b,]
	gamInit = gamInit1[,,b]

	return (list(phiInit=phiInit, rhoInit=rhoInit, piInit=piInit, gamInit=gamInit))
}